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This paper aims to conduct a systematic literature review of the research in the field of Artificial Intelligence (AI) and Big Data Analytics (BDA) in Supply Chain Risk Management (SCRM). Finally, future research directions in this field have been suggested.

The papers were searched using a set of keywords in the SCOPUS database. These papers were filtered using the Title abstract keywords principle. Further, more papers were found using the forward-backward referencing method. The finalized papers were then classified into eight categories.

The previous papers in AI and BDA in SCRM were studied. These papers emphasized various modelling and application techniques for AI and BDA in making the supply chain (SC) more resilient. It was found that more research has been done into conceptual modelling rather than real-life applications. It was seen that the use of AI-based techniques and structural equation modelling was prominent.

AI and BDA help build the risk profile, which will guide the decision-makers and risk managers make their decisions quickly and more effectively, reducing the risks on the SC and making it resilient. Other than this, they can predict the risks in disasters, epidemics and any further disruption. They also help select the suppliers and location of the various elements of the SC to reduce the lead times.

The paper suggests various future research directions that fellow researchers can explore. None of the previous research examined the role of BDA and AI in SCRM.

This research addresses the relationships between the current, dynamic organisational cyber risk climate, organisational cybersecurity performance and changes in cybersecurity investments, with an aim to address the hostile epistemic climate for intellectual capital management presented by the dynamics of cybersecurity as a phenomenon.

Expanding on the views of digital security and resilience as a knowledge problem, the research looks at cybersecurity as a critical capability within organisations, particularly relevant in critical infrastructure sectors. The problem is studied from the perspective of 400 C-level executives from critical infrastructure sectors across the UK. Data collected at the peak of the coronavirus disease 2019 (COVID-19) pandemic, a time when critical infrastructure organisations have been under a significant strain due to an increase in cybersecurity incidents, were analysed using partial least square structural equation modelling.

The research found a significant correlation between the board's perception of a change in their cybersecurity risk climate and patterns of both the development of cybersecurity management capabilities and cybersecurity investments. The authors also found that a positive correlation exists between the efforts placed by critical infrastructure organisations in cybersecurity training and the changes in investment in their cybersecurity, particularly in relation to their intellectual capital development efforts.

To the best of the authors’ knowledge, this is the first paper that explores the board's perception of cybersecurity in critical infrastructure organisations both from the intellectual capital perspective and in the dynamic cyber risk climate derived from the COVID-19 crisis. The authors’ findings expand on the growing perception of cybersecurity as a knowledge problem, and thus inform future research and practice in the domain of intellectual capital management and its role in supporting the cybersecurity and digital resilience of business and society.

The purpose of this article is to compare design choices and assess the structural complexity of six manufacturing supply chains (SCs) of the Brazilian wind turbine industry.

The research method is quantitative modeling. This study adopts the social network perspective to provide a broad set of network metrics for comparative analysis and characterization of the structural configuration and complexity of SCs. Transaction costs and the risk of disruption supported the metrics employed in the study. Network size, network density, core-size and centralization metrics stem from transaction costs, whereas constraint and betweenness centrality stem from risk of disruption.

The main conclusion is that, in the Brazilian wind manufacturing industry, increasing the SC structural complexity by adding redundant ties to minimize disruption risks, even implying higher transaction costs, increases the capacity to win orders.

Only the Brazilian wind turbine industry was studied. Therefore, findings are not general, but specific, to the case.

Managers and practitioners of the Brazilian wind turbine industry should focus on increasing the complexity of their SCs, even if it increases transaction costs, to ensure due dates compliance in orders.

To the best of the available knowledge, there is no commonly accepted or shared measurement for SC complexity, and this study proposed an alternative approach to bridge this research gap, the structural perspective of social networks. Traditional measures were complemented by new metrics, and the power of the application of social network analysis to SC investigations was empirically demonstrated in different levels of analysis.

Catastrophic supply chain disruptions can significantly damage the operational and financial performance of firms. While a growing body of literature on supply network structures has studied what influences supply networks' vulnerability to supply chain disruptions and capability to recover from them, it remains unclear how supply network structures change after major supply chain disruptions. We aim to provide an understanding of how these changes occur.

Using a natural experiment approach and supply network data from Factset, this study investigates how firms' supply network structures change after experiencing the catastrophic supply chain disruptions caused by the 2011 Tohoku earthquake and tsunami in Japan. We capture post-earthquake supply network changes using the measures of degree centrality and ego network density.

The results of the analysis suggest that compared to unaffected firms, the affected firms experience changes in their supply network structures tending toward lower complexity measured by in-degree centrality, out-degree centrality and ego network density.

This study contributes to social network theory and the complex adaptive supply network literature by providing empirical evidence of structural changes in supply networks after catastrophic supply chain disruptions. A managerial contribution is made by providing a reflection on why these changes might be occurring and alert firms to the challenges of managing complexity in their supply networks.

The purpose of this paper is to develop a conceptual framework for the analysis of supply network disruptions and present a number of propositions to define a future research agenda. In doing so, it draws on a review of the literature regarding supply chain disruptions; relationship formation and evolution; and network formation and evolution.

The literature review combined traditional contextual analysis with citation analysis and co‐citation, assuming a multi‐level, multi‐theoretical perspective.

The findings highlight a paucity of empirical research regarding supply chain disruptions assuming a network perspective, highlighting the dynamic nature of networks and emphasising the difference between supply chain disturbance and disruption.

The paper stops short of testing specific hypotheses, providing a conceptual framework and a series of propositions from which testable hypotheses can be developed. The necessity of assuming a dynamic, multi‐level, multi‐theoretical perspective highlights the difficulties of empirical research in this area. However, the significance of understanding the network context of disruption and its connection to the securing of appropriate responses and ultimately reasonable mitigation is unavoidable.

The ability to understand the implications of network structure and network relational dynamics in the context of disruption will enable managers to respond appropriately to disruptive supply chain events. This capability will assume increasing importance in the vulnerable and sensitive global economy.

The paper's specific consideration of disruption (as opposed to disturbance), and the necessitated speed of response leads to the development of several disruption‐specific propositions and the development of a new research agenda.

This paper provides a practical framework for managers to develop a sustainable supply chain. Given that rapid globalization has increased supply disruption risk, managers have been forced to establish efficient and responsive supply chain strategies. Nevertheless, diverse uncertainty factors, such as risk perception of strategies, have made practical management difficult. Quantifying managers' risk perceptions and applying them to supply chain strategies allows the authors to propose a structural and practical model for managing supply disruption.

The existing structural model is refined by taking subjective factors into account using the analytic hierarchy process. The applicability of the refined model is demonstrated through a comparative case study.

Managers' risk perceptions vary not only among companies but also between managing divisions within a company, which necessitates possible changes in strategy due to environmental turbulence. The principal component analysis (PCA) characterizes managers' risk perceptions that illustrate companies' emphases on disruption risk.

The proposed approach quantifies risk perception, which enables practitioners to deal with subjective information in quantitative form. Comparative studies clarify differences in perception given different business backgrounds. The results provide managers with in-depth insights for establishing supply chain strategies reflecting their risk perception.

Quantification of managers' subjective risk perception clarifies both the trend and the individual features for uncertainties. The results allow the authors to conduct the PCA, which characterizes companies. Comparative studies generalize the results of extant work, shedding light on cross-sectional differences given different business backgrounds. The effectiveness of the approach is confirmed through retrospective interviews with practitioners.

The purpose of this study is to examine supplier financial risk through the lens of Enactment Theory, to explore the role of transparency and communication on buyers’ perceptions of supplier default risk. The authors develop a theoretical model proposing that buyer communication with suppliers leads to preemptive actions that may prevent supplier financial default and fewer supply disruptions. The results suggest that reducing equivocality in buyers through communication with suppliers leads to understanding of financial factors not captured through third-party financial indicators, leading to proactive risk mitigation activities that prevent disruptions during recessionary economic cycles. This research proposes that transparency and communication reduces equivocality in buyers, spurring them to take contractual actions that reduces, financial default in key suppliers, which leads to fewer supply disruptions.

Survey data collected from 175 firms in the North America and Brazil during a period of the global recession is used to test the impact of communication with suppliers on supply chain disruptions in periods of economic crisis. This relationship is mediated by proactive contract renegotiation and supplier financial health, supporting a model grounded in Enactment Theory.

Results show that buyers who regularly assess and develop an understanding of their key suppliers’ financial conditions are more likely to re-negotiate contracts that revise payment terms, leading to improved supplier working capital and fewer supply chain disruptions.

Validation of industry-specific financial ratios and figures could provide a richer set of insights and some quantitative measures for establishing baseline on what levels of financial ratios actually result in disruptions. However, future research should consider using a cross-sectional sample and, in addition, a qualitative approach to capture risk from a greater variety of industries and supply chain dynamics.

The notion of effective communication flows as a means for reduction of supplier disruption risk is aligned with Enactment Theory views that emphasize the benefits of risk reduction. Equivocality is reduced in buyers through information exchange and formal assessments in complex environments. This research suggests that while such communication does not have a direct effect on supply disruption risk, it is mediated through proactive buyer actions to improve supplier financial health and contract re-negotiation mechanisms that may preempt financial distress. These are important lessons learned that provide guidelines for supply chain executives in future economic recessions that may occur in the coming years.

The purpose of this paper is to create a resilient supply chain (SC) plan to contain disruptions and risks in the overall operations of a business.

The study integrates resilience considerations in a business planning model that formulates resilience performance (RP) of SC functions in terms of flexibility, reliability, and similar system factors. It evaluates the RP of SC plans and determines their vulnerability considering required and planned resources. The model estimates the possible effects of disasters on vulnerable functions using a scenario-based analysis and plans containment options. It also includes decision options for deploying resources to achieve the expected levels of resilience by preventing potential vulnerabilities. The model takes optimum decision in a what-if approach by comparing performance of the existing business plan, with options for containing the vulnerabilities inherent in not considering potential risks when planning to fulfill market demand, and the performance of a resilient plan that includes decision options to prevent vulnerabilities where possible and mitigate them otherwise.

It is possible, for example, to evaluate RP of SC plans, identify vulnerable functions, and decide optimum option to create resilient business system.

The present study takes a generic approach and creates bases to explore its application in any industry-based case.

The research introduces formulations for RPs and vulnerability indices that can be included in a planning model to create a resilient SC.